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This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.

This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.

Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.

Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.

A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.

Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.

The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.

The purpose of this paper is to introduce the concept of meaning as a relevant but missing link in understanding the building blocks of service innovation informed by service-dominant (S-D) logic. In exploring the role of meaning in service innovation, especially related to new value propositions, resource integration and new value cocreation, the authors suggest using the conceptualization of meaning within human-centered design, which has an established body of knowledge on addressing how actors engage and interact.

The paper builds an actionable conceptual framework that relates meaning to central tenets of service innovation, such as resource integration, value propositions and cocreation of value. It delineates the central building blocks of service innovation and conceptually integrates them with meaning to explain the underlying mechanisms of service innovation related both to its development and adoption.

The findings highlight how and why meaning precedes value creation and directs resource integration. Indicating that meaning is driven by experience of earlier interactions it delineates its relationships with new value formation and positions resource interpretation as a driver of this process.

This paper extends the understanding of service innovation in relation to S-D logic, with meaning as a conceptual link to aspects of S-D logic that claim a phenomenological nature. Meaning contributes to S-D logic by providing an understanding of how beneficiaries form intentions to engage in value creation and resource integration. Additionally, by integrating service and design research domains, this paper suggests possibilities for multidisciplinary contributions in future research.

Research into the interpretability and explainability of data analytics and artificial intelligence (AI) systems is on the rise. However, most recent studies either solely promote the benefits of explainability or criticize it due to its counterproductive effects. This study addresses this polarized space and aims to identify opposing effects of the explainability of AI and the tensions between them and propose how to manage this tension to optimize AI system performance and trustworthiness.

The author systematically reviews the literature and synthesizes it using a contingency theory lens to develop a framework for managing the opposing effects of AI explainability.

The author finds five opposing effects of explainability: comprehensibility, conduct, confidentiality, completeness and confidence in AI (5Cs). The author also proposes six perspectives on managing the tensions between the 5Cs: pragmatism in explanation, contextualization of the explanation, cohabitation of human agency and AI agency, metrics and standardization, regulatory and ethical principles, and other emerging solutions (i.e. AI enveloping, blockchain and AI fuzzy systems).

As in other systematic literature review studies, the results are limited by the content of the selected papers.

The findings show how AI owners and developers can manage tensions between profitability, prediction accuracy and system performance via visibility, accountability and maintaining the “social goodness” of AI. The results guide practitioners in developing metrics and standards for AI explainability, with the context of AI operation as the focus.

This study addresses polarized beliefs amongst scholars and practitioners about the benefits of AI explainability versus its counterproductive effects. It poses that there is no single best way to maximize AI explainability. Instead, the co-existence of enabling and constraining effects must be managed.

This paper investigates effective human-robot collaboration (HRC) and presents implications for Human Resource Management (HRM). A brief review of current literature on HRM in the smart industry context showed that there is limited research on HRC in hybrid teams and even less on effective management of these teams. This book chapter addresses this issue by investigating factors affecting intention to collaborate with a robot by conducting a vignette study. We hypothesized that six technology acceptance factors, performance expectancy, trust, effort expectancy, social support, organizational support and computer anxiety would significantly affect a users' intention to collaborate with a robot. Furthermore, we hypothesized a moderating effect of a particular HR system, either productivity-based or collaborative. Using a sample of 96 participants, this study tested the effect of the aforementioned factors on a users' intention to collaborate with the robot. Findings show that performance expectancy, organizational support and computer anxiety significantly affect the intention to collaborate with a robot. A significant moderating effect of a particular HR system was not found. Our findings expand the current technology acceptance models in the context of HRC. HRM can support effective HRC by a combination of comprehensive training and education, empowerment and incentives supported by an appropriate HR system.

This study aims to analyse the differences between professional interaction mediated by video conferencing and direct professional interaction. The research identifies diverging interests of office workers for the purpose of addressing work ethical and business ethical issues of professional collaboration, competition, and power in future hybrid work models.

Based on 28 qualitative interviews conducted between November 2020 and June 2021, and through the theoretical lens of phenomenology, the study develops explanatory hypotheses conceptualising four basic intentions of professional interaction and their corresponding preferences for video conferences and working on site.

The four intentions developed on the basis of the interviews are: the need for physical proximity; the challenge of collective creativity; the will to influence; and control of communication. This conceptual framework qualifies a moral ambivalence of professional interaction. The authors identify a connectivity paradox of professional interaction where the personal dimension remains unarticulated for the purpose of maintaining professionality. This tacit human connectivity is intertwined with latent power relations. This plasticity of both connectivity and power in direct interaction can be diminished by transferring the interaction to video conferencing.

The application of phenomenology to a collection of qualitative interviews has enabled the identification of underlying intention structures and the system in which they affect each other. This research identifies conflicts of interests between workers relative to their different self-perceived abilities to persevere in competitive professional interaction. It is therefore able to address consequences of future hybrid work models at an existential and societal level.

This study introduces an ecological framework for disabilities meant to provide a new model of viewing and learning about disabilities and special education. This model projects a multi-systemic view of factors that influence a person's life, where people with disabilities are active actors in the development of the world. The increased awareness about interconnectedness, globalization, inter- and trans-disciplinarity, influences on human experience, greening, sustainability, inequality, inequity and lack of opportunities is shifting how people think about potential and growth.

The methodological approach is qualitative, interpretive research.

In disability studies, the Ecological Model of Disabilities helps reframe this uniqueness as part of the spectrum of human experiences. In special education, the Ecoducation Model helps reframe the learning experience.

This research is conceptual, but it is also all-inclusive, rendering itself to a wide application in educational settings.

The Ecoducation Model for Special Education is specific to the education of children and adults with disabilities, and it is directly compatible with the broader Ecological Model of Disabilities. These ecological models can be applied to all levels of the ecological system, and to different ecodemes of population. Nevertheless, the ecological models need to be locally implemented, with general principles tailored to national traditions, laws and resources.

Advocating for the pursuit of individual well-being within the larger society, both models call for practical changes in a multitude of areas, including legislation and policy, training of professional personnel, sufficient financial input in programs designed for the care of children and adults with disabilities, change in societal mentalities to fight discrimination, disempowerment and isolation. Because the scope of ecological frameworks is incommensurate, being both interdisciplinary and transdisciplinary, further research possibilities are countless. The ecological perspective opens the fields of disability studies and special education to new theoretical and empirical possibilities.

Two epistemological models are described as new frameworks in disability studies: the Ecological Model of Disabilities and the Ecoducation Model for Special Education. Both are original models that look into the education and inclusion of the person with disabilities.

This paper aims to determine the status of the socialist market economy through a logical analysis of the evolution of economic systems in human society.

This paper presents an analysis of uncertainty and the functions performed by different economic systems in managing and resolving it, thereby explaining the evolutionary rationale behind economic system evolution.

Firstly, the socialist market economy empowers the market to play a decisive role in resource allocation, which serves as the foundation for activating individuals' motivation to engage in economic activities. Secondly, the socialist market economy adheres to the basic socialist economic system, which is the basis for the socialist market economy to stabilize the economy and society or to address the risk of economic uncertainty that may trigger macro-level inconsistencies in economic operations. Thirdly, the advantages of a socialist market economy in adapting to economic uncertainties do not arise spontaneously and must be exerted through continuous improvement of the socialist market economy.

The innovation of this paper lies in introducing uncertainty to clarify the logic behind the evolution of economic systems in human society and explaining the typical significance of the socialist market economy and its advantages in accommodating and resolving uncertainty.